corr_ti&shap

setwd("/Users/aubrey/Documents/SHK/randomness-as-regularization/Treeinterpreter")
getwd()

## [1] "/Users/aubrey/Documents/SHK/randomness-as-regularization/Treeinterpreter"

library(ggplot2)

dataname <- c('abalone', 'bike', 'boston', 'concrete', 'cpu', 'csm', 'fb', 'parkinsons','servo', 'solar','synthetic')
Cor_pearson <- c()
Cor_spearman <- c()
for(i in dataname){
  ti <- read.csv(file = paste0('ti_',i,'.csv'))[,-c(1)]
  shap <- read.csv(file = paste0('shap_',i,'.csv'))[,-c(1)]
  for(j in colnames(ti)){
    Cor_pearson <- c(Cor_pearson,as.numeric(cor(ti[j], shap[j])))
    Cor_spearman <- c(Cor_spearman,as.numeric(cor(ti[j], shap[j])))
    print(paste0("The pearson correlation of treeinterpreter and shap value in ",i," with regard to ", j, " is ", round(cor(ti[j], shap[j]), digits = 4)))
    print(paste0("The spearman correlation of treeinterpreter and shap value in  ",i," with regard to ", j, " is ", round(cor(ti[j], shap[j], method = 'spearman'), digits = 4)))
    temp <- data.frame(c(ti[j],shap[j]))
    colnames(temp) <- c("ti","shap")
    # Basic scatter plot
    print(ggplot(temp, aes(x=ti, y=shap)) + geom_point() +
      geom_smooth()+
      geom_smooth(method='lm', color='red')+
      labs(title=paste0("The scatter plot of treeinterpreter and shap value in ",i," with regard to ", j),
       x=paste0("ti_",i,"_",j), y = paste0("shap_",i,"_",j)))
  }
}

## [1] "The pearson correlation of treeinterpreter and shap value in abalone with regard to Sex_I is 0.9003"
## [1] "The spearman correlation of treeinterpreter and shap value in  abalone with regard to Sex_I is 0.9083"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'

## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in abalone with regard to Sex_M is 0.8145"
## [1] "The spearman correlation of treeinterpreter and shap value in  abalone with regard to Sex_M is 0.7622"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in abalone with regard to Length is 0.9187"
## [1] "The spearman correlation of treeinterpreter and shap value in  abalone with regard to Length is 0.8918"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in abalone with regard to Diameter is 0.9387"
## [1] "The spearman correlation of treeinterpreter and shap value in  abalone with regard to Diameter is 0.9074"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in abalone with regard to Height is 0.9529"
## [1] "The spearman correlation of treeinterpreter and shap value in  abalone with regard to Height is 0.9458"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in abalone with regard to WholeWeight is 0.8722"
## [1] "The spearman correlation of treeinterpreter and shap value in  abalone with regard to WholeWeight is 0.8739"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in abalone with regard to ShuckedWeight is 0.825"
## [1] "The spearman correlation of treeinterpreter and shap value in  abalone with regard to ShuckedWeight is 0.8498"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in abalone with regard to VisceraWeight is 0.938"
## [1] "The spearman correlation of treeinterpreter and shap value in  abalone with regard to VisceraWeight is 0.9124"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in abalone with regard to ShellWeight is 0.9748"
## [1] "The spearman correlation of treeinterpreter and shap value in  abalone with regard to ShellWeight is 0.9753"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in bike with regard to season is 0.9605"
## [1] "The spearman correlation of treeinterpreter and shap value in  bike with regard to season is 0.9026"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in bike with regard to yr is 0.9921"
## [1] "The spearman correlation of treeinterpreter and shap value in  bike with regard to yr is 0.9102"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in bike with regard to mnth is 0.855"
## [1] "The spearman correlation of treeinterpreter and shap value in  bike with regard to mnth is 0.832"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in bike with regard to holiday is 0.9354"
## [1] "The spearman correlation of treeinterpreter and shap value in  bike with regard to holiday is 0.9128"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in bike with regard to weekday is 0.9238"
## [1] "The spearman correlation of treeinterpreter and shap value in  bike with regard to weekday is 0.8922"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in bike with regard to workingday is 0.9259"
## [1] "The spearman correlation of treeinterpreter and shap value in  bike with regard to workingday is 0.8386"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in bike with regard to weathersit is 0.942"
## [1] "The spearman correlation of treeinterpreter and shap value in  bike with regard to weathersit is 0.9184"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in bike with regard to temp is 0.9889"
## [1] "The spearman correlation of treeinterpreter and shap value in  bike with regard to temp is 0.9617"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in bike with regard to atemp is 0.9575"
## [1] "The spearman correlation of treeinterpreter and shap value in  bike with regard to atemp is 0.963"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in bike with regard to hum is 0.9632"
## [1] "The spearman correlation of treeinterpreter and shap value in  bike with regard to hum is 0.9519"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in bike with regard to windspeed is 0.9164"
## [1] "The spearman correlation of treeinterpreter and shap value in  bike with regard to windspeed is 0.8942"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in boston with regard to crim is 0.9653"
## [1] "The spearman correlation of treeinterpreter and shap value in  boston with regard to crim is 0.9316"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in boston with regard to zn is 0.8846"
## [1] "The spearman correlation of treeinterpreter and shap value in  boston with regard to zn is 0.7627"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in boston with regard to indus is 0.9339"
## [1] "The spearman correlation of treeinterpreter and shap value in  boston with regard to indus is 0.8031"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in boston with regard to chas is 0.9056"
## [1] "The spearman correlation of treeinterpreter and shap value in  boston with regard to chas is 0.8026"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in boston with regard to nox is 0.9625"
## [1] "The spearman correlation of treeinterpreter and shap value in  boston with regard to nox is 0.8035"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in boston with regard to rm is 0.9876"
## [1] "The spearman correlation of treeinterpreter and shap value in  boston with regard to rm is 0.9075"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in boston with regard to age is 0.9114"
## [1] "The spearman correlation of treeinterpreter and shap value in  boston with regard to age is 0.9105"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in boston with regard to dis is 0.931"
## [1] "The spearman correlation of treeinterpreter and shap value in  boston with regard to dis is 0.8851"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in boston with regard to rad is 0.7754"
## [1] "The spearman correlation of treeinterpreter and shap value in  boston with regard to rad is 0.4879"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in boston with regard to tax is 0.936"
## [1] "The spearman correlation of treeinterpreter and shap value in  boston with regard to tax is 0.9014"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in boston with regard to ptratio is 0.9551"
## [1] "The spearman correlation of treeinterpreter and shap value in  boston with regard to ptratio is 0.9342"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in boston with regard to b is 0.9292"
## [1] "The spearman correlation of treeinterpreter and shap value in  boston with regard to b is 0.9143"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in boston with regard to lstat is 0.9576"
## [1] "The spearman correlation of treeinterpreter and shap value in  boston with regard to lstat is 0.9626"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in concrete with regard to Cement..component.1..kg.in.a.m.3.mixture. is 0.9904"
## [1] "The spearman correlation of treeinterpreter and shap value in  concrete with regard to Cement..component.1..kg.in.a.m.3.mixture. is 0.991"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in concrete with regard to Blast.Furnace.Slag..component.2..kg.in.a.m.3.mixture. is 0.9455"
## [1] "The spearman correlation of treeinterpreter and shap value in  concrete with regard to Blast.Furnace.Slag..component.2..kg.in.a.m.3.mixture. is 0.9509"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in concrete with regard to Fly.Ash..component.3..kg.in.a.m.3.mixture. is 0.9244"
## [1] "The spearman correlation of treeinterpreter and shap value in  concrete with regard to Fly.Ash..component.3..kg.in.a.m.3.mixture. is 0.8483"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in concrete with regard to Water...component.4..kg.in.a.m.3.mixture. is 0.9777"
## [1] "The spearman correlation of treeinterpreter and shap value in  concrete with regard to Water...component.4..kg.in.a.m.3.mixture. is 0.951"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in concrete with regard to Superplasticizer..component.5..kg.in.a.m.3.mixture. is 0.9598"
## [1] "The spearman correlation of treeinterpreter and shap value in  concrete with regard to Superplasticizer..component.5..kg.in.a.m.3.mixture. is 0.9462"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in concrete with regard to Coarse.Aggregate...component.6..kg.in.a.m.3.mixture. is 0.9166"
## [1] "The spearman correlation of treeinterpreter and shap value in  concrete with regard to Coarse.Aggregate...component.6..kg.in.a.m.3.mixture. is 0.8798"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in concrete with regard to Fine.Aggregate..component.7..kg.in.a.m.3.mixture. is 0.9366"
## [1] "The spearman correlation of treeinterpreter and shap value in  concrete with regard to Fine.Aggregate..component.7..kg.in.a.m.3.mixture. is 0.9198"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in concrete with regard to Age..day. is 0.9907"
## [1] "The spearman correlation of treeinterpreter and shap value in  concrete with regard to Age..day. is 0.9621"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_amdahl is 0.8798"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_amdahl is 0.6356"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_apollo is 0.9947"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_apollo is 0.8831"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_basf is 0.9933"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_basf is 0.908"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_bti is 0.9511"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_bti is 0.8444"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_burroughs is 0.8902"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_burroughs is 0.7131"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_c.r.d is 0.9885"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_c.r.d is 0.9231"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_cambex is 0.9457"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_cambex is 0.7743"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_cdc is 0.8996"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_cdc is 0.6922"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_dec is 0.9825"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_dec is 0.8779"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_dg is 0.9834"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_dg is 0.939"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_formation is 0.9946"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_formation is 0.9406"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_four.phase is 0.9765"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_four.phase is 0.7673"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_gould is 0.9888"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_gould is 0.8677"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_harris is 0.9718"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_harris is 0.9273"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_honeywell is 0.8837"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_honeywell is 0.7911"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_hp is 0.8949"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_hp is 0.6996"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_ibm is 0.8729"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_ibm is 0.6009"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_ipl is 0.5885"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_ipl is 0.7742"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_magnuson is 0.9908"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_magnuson is 0.865"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_microdata is 0.9944"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_microdata is 0.6826"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_nas is 0.9562"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_nas is 0.7504"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_ncr is 0.9769"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_ncr is 0.9188"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_nixdorf is 0.9905"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_nixdorf is 0.9454"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_perkin.elmer is 0.984"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_perkin.elmer is 0.837"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_prime is 0.9809"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_prime is 0.884"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_siemens is 0.855"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_siemens is 0.8443"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_sperry is 0.9802"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_sperry is 0.9265"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_sratus is 0.9961"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_sratus is 0.8576"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to vendor_wang is 0.9678"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to vendor_wang is 0.968"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to MYCT is 0.946"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to MYCT is 0.9277"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to MMIN is 0.9587"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to MMIN is 0.9346"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to MMAX is 0.9859"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to MMAX is 0.9163"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to CACH is 0.952"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to CACH is 0.8569"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to CHMIN is 0.9537"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to CHMIN is 0.8495"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in cpu with regard to CHMAX is 0.9726"
## [1] "The spearman correlation of treeinterpreter and shap value in  cpu with regard to CHMAX is 0.9102"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in csm with regard to Genre is 0.9923"
## [1] "The spearman correlation of treeinterpreter and shap value in  csm with regard to Genre is 0.8848"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in csm with regard to Budget is 0.979"
## [1] "The spearman correlation of treeinterpreter and shap value in  csm with regard to Budget is 0.9019"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in csm with regard to Screens is 0.9714"
## [1] "The spearman correlation of treeinterpreter and shap value in  csm with regard to Screens is 0.9579"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in csm with regard to Sequel is 0.9316"
## [1] "The spearman correlation of treeinterpreter and shap value in  csm with regard to Sequel is 0.9071"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in csm with regard to Sentiment is 0.96"
## [1] "The spearman correlation of treeinterpreter and shap value in  csm with regard to Sentiment is 0.9435"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in csm with regard to Views is 0.9098"
## [1] "The spearman correlation of treeinterpreter and shap value in  csm with regard to Views is 0.9119"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in csm with regard to Likes is 0.96"
## [1] "The spearman correlation of treeinterpreter and shap value in  csm with regard to Likes is 0.9428"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in csm with regard to Dislikes is 0.9789"
## [1] "The spearman correlation of treeinterpreter and shap value in  csm with regard to Dislikes is 0.9655"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in csm with regard to Comments is 0.9535"
## [1] "The spearman correlation of treeinterpreter and shap value in  csm with regard to Comments is 0.953"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in csm with regard to Aggregate.Followers is 0.9517"
## [1] "The spearman correlation of treeinterpreter and shap value in  csm with regard to Aggregate.Followers is 0.9564"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in fb with regard to Type_Photo is 0.7901"
## [1] "The spearman correlation of treeinterpreter and shap value in  fb with regard to Type_Photo is 0.7189"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in fb with regard to Type_Status is 0.5731"
## [1] "The spearman correlation of treeinterpreter and shap value in  fb with regard to Type_Status is 0.6888"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in fb with regard to Type_Video is 0.9835"
## [1] "The spearman correlation of treeinterpreter and shap value in  fb with regard to Type_Video is 0.7775"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in fb with regard to Page.total.likes is 0.9365"
## [1] "The spearman correlation of treeinterpreter and shap value in  fb with regard to Page.total.likes is 0.8247"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in fb with regard to Category is 0.9106"
## [1] "The spearman correlation of treeinterpreter and shap value in  fb with regard to Category is 0.9266"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in fb with regard to Post.Month is 0.9203"
## [1] "The spearman correlation of treeinterpreter and shap value in  fb with regard to Post.Month is 0.8831"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in fb with regard to Post.Weekday is 0.9378"
## [1] "The spearman correlation of treeinterpreter and shap value in  fb with regard to Post.Weekday is 0.8852"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in fb with regard to Post.Hour is 0.9534"
## [1] "The spearman correlation of treeinterpreter and shap value in  fb with regard to Post.Hour is 0.9009"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in fb with regard to Paid is 0.8501"
## [1] "The spearman correlation of treeinterpreter and shap value in  fb with regard to Paid is 0.8086"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to subject. is 0.969"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to subject. is 0.9462"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to age is 0.9558"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to age is 0.9646"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to sex is 0.8942"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to sex is 0.904"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to test_time is 0.9189"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to test_time is 0.9204"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to Jitter... is 0.8389"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to Jitter... is 0.7516"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to Jitter.Abs. is 0.899"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to Jitter.Abs. is 0.8232"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to Jitter.RAP is 0.8009"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to Jitter.RAP is 0.7795"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to Jitter.PPQ5 is 0.8018"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to Jitter.PPQ5 is 0.7717"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to Jitter.DDP is 0.7933"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to Jitter.DDP is 0.7527"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to Shimmer is 0.7654"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to Shimmer is 0.724"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to Shimmer.dB. is 0.7742"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to Shimmer.dB. is 0.7411"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to Shimmer.APQ3 is 0.8202"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to Shimmer.APQ3 is 0.7679"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to Shimmer.APQ5 is 0.7716"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to Shimmer.APQ5 is 0.7284"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to Shimmer.APQ11 is 0.7202"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to Shimmer.APQ11 is 0.7085"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to Shimmer.DDA is 0.8045"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to Shimmer.DDA is 0.7803"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to NHR is 0.7726"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to NHR is 0.7059"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to HNR is 0.9094"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to HNR is 0.8083"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to RPDE is 0.8701"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to RPDE is 0.8226"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to DFA is 0.9127"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to DFA is 0.8747"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in parkinsons with regard to PPE is 0.8885"
## [1] "The spearman correlation of treeinterpreter and shap value in  parkinsons with regard to PPE is 0.912"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in servo with regard to motor_B is 0.9196"
## [1] "The spearman correlation of treeinterpreter and shap value in  servo with regard to motor_B is 0.6292"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in servo with regard to motor_C is 0.9287"
## [1] "The spearman correlation of treeinterpreter and shap value in  servo with regard to motor_C is 0.8535"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in servo with regard to motor_D is 0.9629"
## [1] "The spearman correlation of treeinterpreter and shap value in  servo with regard to motor_D is 0.9397"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in servo with regard to motor_E is 0.9395"
## [1] "The spearman correlation of treeinterpreter and shap value in  servo with regard to motor_E is 0.802"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in servo with regard to screw_B is 0.9388"
## [1] "The spearman correlation of treeinterpreter and shap value in  servo with regard to screw_B is 0.929"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in servo with regard to screw_C is 0.9508"
## [1] "The spearman correlation of treeinterpreter and shap value in  servo with regard to screw_C is 0.9328"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in servo with regard to screw_D is 0.9491"
## [1] "The spearman correlation of treeinterpreter and shap value in  servo with regard to screw_D is 0.9326"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in servo with regard to screw_E is 0.9578"
## [1] "The spearman correlation of treeinterpreter and shap value in  servo with regard to screw_E is 0.958"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in servo with regard to pgain is 0.9817"
## [1] "The spearman correlation of treeinterpreter and shap value in  servo with regard to pgain is 0.7621"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in servo with regard to vgain is 0.8656"
## [1] "The spearman correlation of treeinterpreter and shap value in  servo with regard to vgain is 0.7547"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to class_C is 0.9066"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to class_C is 0.7987"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to class_D is 0.8324"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to class_D is 0.7061"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to class_E is 0.9589"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to class_E is 0.4633"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to class_F is 0.9594"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to class_F is 0.4819"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to class_H is 0.9543"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to class_H is 0.7026"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to largest.spot.size_H is 0.9695"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to largest.spot.size_H is 0.8458"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to largest.spot.size_K is 0.9688"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to largest.spot.size_K is 0.9113"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to largest.spot.size_R is 0.9494"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to largest.spot.size_R is 0.9293"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to largest.spot.size_S is 0.8662"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to largest.spot.size_S is 0.7956"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to largest.spot.size_X is 0.9568"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to largest.spot.size_X is 0.819"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to spot.distribution_I is 0.8436"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to spot.distribution_I is 0.7847"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to spot.distribution_O is 0.8289"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to spot.distribution_O is 0.8641"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to spot.distribution_X is 0.9537"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to spot.distribution_X is 0.6486"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to Activity is 0.9414"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to Activity is 0.7197"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to Evolution is 0.9539"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to Evolution is 0.8997"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to Previous.24.hour.flare.activity.code is 0.9593"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to Previous.24.hour.flare.activity.code is 0.5778"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to Historically.complex is 0.8702"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to Historically.complex is 0.7172"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to Did.region.become.historically.complex is 0.9246"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to Did.region.become.historically.complex is 0.6265"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to Area is 0.8973"
## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to Area is 0.3725"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## Warning in cor(ti[j], shap[j]): the standard deviation is zero

## Warning in cor(ti[j], shap[j]): the standard deviation is zero

## Warning in cor(ti[j], shap[j]): the standard deviation is zero

## [1] "The pearson correlation of treeinterpreter and shap value in solar with regard to Area.of.the.largest.spot is NA"

## Warning in cor(ti[j], shap[j], method = "spearman"): the standard deviation is
## zero

## [1] "The spearman correlation of treeinterpreter and shap value in  solar with regard to Area.of.the.largest.spot is NA"

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in synthetic with regard to X1 is 0.9834"
## [1] "The spearman correlation of treeinterpreter and shap value in  synthetic with regard to X1 is 0.9718"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in synthetic with regard to X2 is 0.9898"
## [1] "The spearman correlation of treeinterpreter and shap value in  synthetic with regard to X2 is 0.9829"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in synthetic with regard to X3 is 0.9971"
## [1] "The spearman correlation of treeinterpreter and shap value in  synthetic with regard to X3 is 0.9906"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in synthetic with regard to X4 is 0.993"
## [1] "The spearman correlation of treeinterpreter and shap value in  synthetic with regard to X4 is 0.9907"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

## [1] "The pearson correlation of treeinterpreter and shap value in synthetic with regard to X5 is 0.9796"
## [1] "The spearman correlation of treeinterpreter and shap value in  synthetic with regard to X5 is 0.9826"

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

Pearson Correlation

summary(Cor_pearson)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.5731  0.8990  0.9457  0.9225  0.9695  0.9971       1

boxplot(Cor_pearson)

Spearman Correlation

summary(Cor_spearman)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.5731  0.8990  0.9457  0.9225  0.9695  0.9971       1

boxplot(Cor_spearman)